Pandas is famously flexible and capable at analyzing numeric data. But Pandas is also flexible and capable at working with times and dates. In this talk, I'll describe the dtypes associated with times and dates, the sorts of calculations you can perform, issues with parsing and importing datetime data, and how you can perform more complex tasks, such as grouping, pivoting, and resampling. By the time this talk is over, you'll be able to work with time-based data in new ways.

times and dates work, from handling inputs to performing sophisticated analysis.